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TEST127aaf287asklearn.ensemble._forest.RandomForestClassifier

TEST127aaf287asklearn.ensemble._forest.RandomForestClassifier

Visibility: public Uploaded 15-01-2024 by Continuous Integration sklearn==0.24.0 numpy>=1.13.3 scipy>=0.19.1 joblib>=0.11 threadpoolctl>=2.0.0 0 runs
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  • openml-python python scikit-learn sklearn sklearn_0.24.0
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A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting. The sub-sample size is controlled with the `max_samples` parameter if `bootstrap=True` (default), otherwise the whole dataset is used to build each tree.

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